By: Joshua Finley

Almost every business in the U.S. is incorporating AI into their strategies. Research from IBM found that 42% of enterprise organizations (over 1,000 employees) actively use AI, and among early adopters, 59% plan to increase their investment in the technology. The versatility and adaptability of generative AI enable its application across various business practices, particularly in enhancing the customer experience.

According to a McKinsey & Company report, companies integrating AI into their customer experience strategies see a 20% increase in customer satisfaction and a 10% reduction in costs. The research highlights that AI’s ability to personalize interactions and provide real-time insights is a key driver of these improvements.

The use of AI to obtain data from customers is fraught with challenges, including the validity of the data and how organizations prioritize data mining results in a way that can lead to actionable strategic shifts. One of the keys to leveraging the power of AI is to choose wisely when it comes to which solution offers the right fit for the organization’s strategic direction – and that can be a daunting task in an environment that is characterized by innovation.

Lihong Hicken, a serial tech entrepreneur and CEO of TheySaid, an innovative conversational AI survey solution aimed at enhancing customer value and revenue, has become a trailblazer in delivering customer insights through AI-driven solutions. After emigrating to the U.S. in 2011, she quickly established a reputation for innovative leadership and a commitment to customer-centric strategies. In addition to her role at TheySaid, she advises early-stage and established companies on effectively interpreting and leveraging customer data.

According to Lihong, AI-driven data can provide exceptional value to the organization. However, her experience has shown that organizations may lack the frameworks to guide how they use data and which data types should be prioritized.

“There’s a lot of hype around AI, but the human element is still important. Customer data comes in various shapes and forms, and it needs to be reinforced by data from other sources. How the organization weighs the sources of data is all-important,” says Lihong  

Prioritizing Data-Based Decision-Making

Customers offer valuable insights that can drive product, service, and business success, but the sheer volume of survey data can often overwhelm companies. Lihong stresses the need for a clear strategy when using this data. She explains, “Effective decision-making starts with strategic alignment. Every survey tool choice, feature, and business decision should align with the company’s strategic goals, ensuring data-driven growth.” 

She also underscores the importance of assigning single ownership to each decision. “In our approach, one person takes full responsibility for the final call. Group-based decisions or ‘vote-style’ choices often lead to unqualified input and can overshadow expertise. Avoid falling into the ‘HIPPO’ trap. Decisions shouldn’t be swayed by the ‘highest-paid person’s opinion.’ Instead, allow the most skilled and experienced team member to lead based on qualified data.”

Lihong advocates for a tiered, data-first approach to decision-making, with customer data at the top, followed by industry insights and team expertise, while personal opinions hold the least weight. “Customer data is our most valuable resource. Decisions must be based on impactful data, and personal opinions need to be set aside. While team insights and industry knowledge matter, we always prioritize data that reflects customer needs.”

Lihong emphasizes the need for all employees to understand the decision-making hierarchy while also having a mechanism for challenging conclusions about data relevance and strategic impact. “If a decision owner is confronted with higher-tier data, such as customer insights or industry benchmarks, they should be encouraged to reassess their decision,” she explains.

AI Insights

Customer insights are vital for shaping products and driving success, but the sheer volume of survey data often overwhelms companies, making actionable insights difficult to extract. AI is transforming this process, helping businesses analyze complex feedback more efficiently and precisely.

“AI allows us to uncover hidden patterns in customer responses that were once buried in data,” says Lihong. “It’s not just sorting information; it’s about gaining insights that drive growth and smarter decisions. Technologies like Natural Language Processing (NLP) craft questions and analyze responses, providing high-quality insights more efficiently than traditional surveys.”

Lihong notes that organizations leveraging AI for customer-focused data analysis can benefit in various ways. “Traditional surveys often demand extensive time and resources, with risks of bias and human error affecting the accuracy of results.” She adds, “AI reshapes this process by generating clear, objective questions and optimizing survey length for efficiency, allowing businesses to move from design to insights much faster.”

Lihong highlights that AI minimizes human bias in data interpretation: “AI is objective and analyzes responses without bias, providing more reliable data and refined insights.” She stresses that choosing the right AI tool is crucial, especially for early-stage companies weighing their return on investment.

“Developing the right tool for the job can be time-consuming and require significant financial investment and expertise; for many early-stage organizations, it can make far more sense to outsource to organizations like TheySaid,” says Lihong. Lihong also emphasizes the adaptability of AI-driven surveys, which enhances engagement and relevance. “Unlike static surveys, AI-powered surveys personalize the experience,” she notes. “They adjust in real-time to responses, leading to more meaningful insights and higher completion rates.” This adaptability allows AI to uncover intricate patterns and forecast future trends that traditional methods often miss.

Lihong’s journey from a small village in China to Silicon Valley exemplifies her resilience and dedication. As the CEO and founder of TheySaid and a Berkeley MBA graduate, she launched her company while balancing the challenges of new motherhood, showcasing her ability to merge innovation with personal responsibilities. With expertise in serial entrepreneurship, customer-focused strategies, and AI-driven solutions, Lihong is a trailblazer transforming how businesses engage with customers.

To learn more about Lihong’s approach to data-driven decision-making, visit her LinkedIn page or personal website. For insights on how TheySaid enhances customer value and revenue, check out the company’s webpage.

Published by: Martin De Juan